version 0.1.0

DESCRIPTION

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+Package: mnet
+Type: Package
+Title: Modeling Group Differences and Moderation Effects in Statistical
+        Network Models
+Version: 0.1.0
+Authors@R: c(
+  person("Jonas", "Haslbeck", email = "jonashaslbeck@protonmail.com",role = c("aut", "cre")))
+Maintainer: Jonas Haslbeck <jonashaslbeck@protonmail.com>
+Description: A toolbox for modeling manifest and latent group differences and moderation effects in various statistical network models.
+BugReports: https://github.com/jmbh/mnet/issues
+Encoding: UTF-8
+LazyData: true
+License: GPL-2
+Imports: mlVAR, doParallel, parallel, foreach
+Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
+VignetteBuilder: knitr
+Config/testthat/edition: 3
+NeedsCompilation: no
+Packaged: 2023-04-22 07:47:31 UTC; jonas
+Author: Jonas Haslbeck [aut, cre]
+Depends: R (>= 3.5.0)
+Repository: CRAN
+Date/Publication: 2023-04-23 15:10:02 UTC

MD5

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+ddd04bab6bb576eb2c518737547fbabb *DESCRIPTION
+1017e4be61f5c9707cb205e8387ec18b *NAMESPACE
+740a1ee1167a1a3e59229b06e42d555f *R/Process_mlVAR.R
+a6f1f6598bcb16f410e40c3555c66f6f *R/mlVAR_GC.R
+e6144c585cc3bdfbe09eacebf49ef687 *R/startup_msg.R
+7f6b535997c2108895480217d1567d8f *README.md
+558206e44deb8fc083352a154910e434 *build/vignette.rds
+364b44dafe67b8c838082045e91246e9 *data/mlVARGD_sim.RData
+d70f8f6ae9980781bbb92f91ea2b1d3d *inst/doc/Vignette_mlVAR_GC.R
+02fed196b3e4947d84301fbb0b67638b *inst/doc/Vignette_mlVAR_GC.Rmd
+63d508f228ac9aff0598cfd31ac56347 *inst/doc/Vignette_mlVAR_GC.html
+556240bcc79df509fccaf408781a6b0d *man/mlVAR_GC.Rd
+c3df94e1654d9f86047c44e091fb89ee *man/mnet-internal.Rd
+308984c7beb11a0d49ff38a388692f20 *tests/testthat.R
+43433c45bd3a5059148ee9945b08558e *tests/testthat/test-mlVAR_GC.R
+02fed196b3e4947d84301fbb0b67638b *vignettes/Vignette_mlVAR_GC.Rmd

NAMESPACE

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+exportPattern("^[[:alpha:]]+")
+
+# Suggested by RMD Check
+importFrom("utils", "setTxtProgressBar", "txtProgressBar")
+importFrom("mlVAR", "mlVAR")
+importFrom("mlVAR", "getNet")
+
+# For parallelization
+import("foreach")
+import("parallel")
+import("doParallel")

R/Process_mlVAR.R

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+# jonashaslbeck@protonmail; April 17, 2023
+
+# ------------------------------------------------------------
+# -------- Function to Process mlVAR Outputs -----------------
+# ------------------------------------------------------------
+
+
+Process_mlVAR <- function(object1,
+                          object2,
+                          contemporaneous = "orthogonal",
+                          temporal = "orthogonal") {
+
+  # Number of vars:
+  p <- ncol(object1$results$Gamma_Omega_mu$mean)
+
+  # a) Between network (using function from mlVAR package)
+  # For very low number of subjects close to the boundary of identifiability
+  # it is possible that lme4 in mlVAR estimates zero variances for random intercepts
+  # which then does not allow one to estimate the between person network
+  # for these cases we set the differences to zero here; later, when calculating
+  # p-values we will just exclude those cases
+
+  if(any(is.na(object1$results$Omega_mu$pcor$mean))) {
+    btw_1 <- matrix(NA, p, p)
+  } else {
+    btw_1 <- mlVAR::getNet(object1, "between", nonsig="show")
+  }
+  if(any(is.na(object2$results$Omega_mu$pcor$mean))) {
+    btw_2 <- matrix(NA, p, p)
+  } else {
+    btw_2 <- mlVAR::getNet(object2, "between", nonsig="show")
+  }
+  btw_diff <- btw_1 - btw_2
+
+  # b.1) VAR: fixed effects
+  phi_fix_1 <- object1$results$Beta$mean
+  phi_fix_2 <- object2$results$Beta$mean
+  phi_fix_diff <- phi_fix_1 - phi_fix_2
+
+  # b.2) VAR: RE sds
+  phi_RE_sd_1 <- object1$results$Beta$SD
+  phi_RE_sd_2 <- object2$results$Beta$SD
+  phi_RE_sd_diff <- phi_RE_sd_1 - phi_RE_sd_2
+
+  # c.1) Contemp: fixed effects
+  Gam_fix_1 <- object1$results$Gamma_Theta$mean
+  Gam_fix_1 <- (Gam_fix_1 + t(Gam_fix_1)) / 2 # Apply AND-rule
+  Gam_fix_2 <- object2$results$Gamma_Theta$mean
+  Gam_fix_2 <- (Gam_fix_2 + t(Gam_fix_2)) / 2 # Apply AND-rule
+  Gam_fix_diff <- Gam_fix_1 - Gam_fix_2
+
+  # c.2) Contemp: RE sds
+  Gam_RE_sd_1 <- object1$results$Gamma_Theta$SD
+  Gam_RE_sd_1 <- (Gam_RE_sd_1 + t(Gam_RE_sd_1)) / 2 # Apply AND-rule
+  Gam_RE_sd_2 <- object2$results$Gamma_Theta$SD
+  Gam_RE_sd_2 <- (Gam_RE_sd_2 + t(Gam_RE_sd_2)) / 2 # Apply AND-rule
+  Gam_RE_sd_diff <- Gam_RE_sd_1 - Gam_RE_sd_2
+
+
+  outlist <- list("diff_between" = btw_diff,
+                  "diff_phi_fix" = phi_fix_diff,
+                  "diff_phi_RE_sd" = phi_RE_sd_diff,
+                  "diff_gam_fix" = Gam_fix_diff,
+                  "diff_gam_RE_sd" = Gam_RE_sd_diff)
+
+  return(outlist)
+
+} # eoF
+
+
+
+